Trauma-informed care implementation in the child- and youth-serving sectors: A scoping review
Bibliographic record
Abstract
Objectives: Enthusiasm for trauma-informed care (TIC) in the child-and youth-serving sectors (CYSSs) has been growing dramatically over the last decade. However, TIC implementation activity on the ground has far outpaced research and the landscape of TIC implementation scholarship is not well known. This scoping review aims to explore: 1) the nature of TIC implementation research in the CYSSs; 2) the characteristics of the change initiatives being studied; 3) the types of evidence these studies have generated; and 4) the gaps in the literature. Methods: On August 28, 2019, the EBSCO, Scopus, Web of Science and PsycINFO databases were searched for English-language, peer-reviewed articles that mentioned “trauma-informed” and (“child” or “children” or “adolescent” or “youth”) in the title, abstract or keywords. Articles selected for this review reported on TIC implementation processes in the CYSSs. Fifty-four articles published between 2004 and 2019 met the inclusion criteria and were reviewed in-depth for this scoping review. Results: High variability was found in the characteristics of TIC implementation research and practice. However, promising preliminary evidence is beginning to show that TIC implementation can lead to a reduction in violent practices and incidents and can improve service provider knowledge, attitude, behaviour and practice (KABP). However, research shows that improvements to self-reports of KABP are often modest, not always maintained over time and not easily translated into actual changes in behaviour, practice and organizational climate due to a variety of barriers. Conclusion: In order to address these barriers, the preliminary evidence suggests that TIC implementation requires a comprehensive approach that includes commitment from senior leadership, ongoing support, and collaboration within and between service providing organizations and systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".